Human Transcriptome Subtraction by Using Short Sequence Tags To Search for Tumor Viruses in Conjunctival Carcinoma

Author:

Feng Huichen1,Taylor Jennifer L.1,Benos Panayiotis V.2,Newton Robert3,Waddell Keith4,Lucas Sebastien B.5,Chang Yuan1,Moore Patrick S.1

Affiliation:

1. Molecular Virology Program, University of Pittsburgh Cancer Institute

2. Departments of Computational Biology and Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania 15213

3. Epidemiology Unit, Radcliffe Infirmary, Cancer Research UK, Gibson Building, Oxford OX2 6HE, United Kingdom

4. Ruharo Eye Hospital, Mbarara

5. Uganda Virus Research Institute, Entebbe, Uganda

Abstract

ABSTRACT Digital transcript subtraction (DTS) was developed to subtract in silico known human sequences from expression library data sets, leaving candidate nonhuman sequences for further analysis. This approach requires precise discrimination between human and nonhuman cDNA sequences. Database comparisons show high likelihood that small viral sequences can be successfully distinguished from human sequences. DTS analysis of 9,026 20-bp tags from an expression library of BCBL-1 cells infected with Kaposi's sarcoma-associated herpesvirus (KSHV) resolved all but three candidate sequences. Two of these sequences belonged to KSHV transcripts, and the third belonged to an unannotated human expression sequence tag. Overall, 0.24% of transcripts from this cell line were of viral origin. DTS analysis of 241,122 expression tags from three squamous cell conjunctival carcinomas revealed that only 21 sequences did not align with sequences from human databases. All 21 candidates amplify human transcripts and have secondary evidence for being of human origin. This analysis shows that it is unlikely that distinguishable viral transcripts are present in conjunctival carcinomas at 20 transcripts per million or higher, which is the equivalent of approximately 4 transcripts per cell. DTS is a simple screening method to discover novel viral nucleic acids. It provides, for the first time, quantitative evidence against some classes of viral etiology when no viral transcripts are found, thereby reducing the uncertainty involved in new pathogen discovery.

Publisher

American Society for Microbiology

Subject

Virology,Insect Science,Immunology,Microbiology

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